Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Support vector machine active learning for image retrieval
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Learning in Content-Based Image Retrieval
ICDL '02 Proceedings of the 2nd International Conference on Development and Learning
Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifiers
Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifiers
A practical SVM-based algorithm for ordinal regression in image retrieval
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Nonparametric Discriminant Analysis in Relevance Feedback for Content-Based Image Retrieval
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Group-based Relevance Feedback with Support Vector Machine Ensembles
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Relevant Data Expansion for Learning Concept Drift from Sparsely Labeled Data
IEEE Transactions on Knowledge and Data Engineering
A Unified Log-Based Relevance Feedback Scheme for Image Retrieval
IEEE Transactions on Knowledge and Data Engineering
Query Reformulation for Content Based Multimedia Retrieval in MARS
ICMCS '99 Proceedings of the 1999 IEEE International Conference on Multimedia Computing and Systems - Volume 02
An image retrieval system with automatic query modification
IEEE Transactions on Multimedia
An interactive approach for CBIR using a network of radial basis functions
IEEE Transactions on Multimedia
Active concept learning in image databases
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Relevance feedback using generalized Bayesian framework with region-based optimization learning
IEEE Transactions on Image Processing
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
Learning a semantic space from user's relevance feedback for image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
Query feedback for interactive image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
A fuzzy combined learning approach to content-based image retrieval
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
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This paper introduces a composite relevance feedback approach for image retrieval using transaction-based and SVM-based learning. A transaction repository is dynamically constructed by applying these two learning techniques on positive and negative session-term feedback. This repository semantically relates each database image to the query images having been used to date. The query semantic feature vector can then be computed using the current feedback and the semantic values in the repository. The correlation measures the semantic similarity between the query image and each database image. Furthermore, the SVM is applied on the session-term feedback to learn the hyperplane for measuring the visual similarity between the query image and each database image. These two similarity measures are normalized and combined to return the retrieved images. Our extensive experimental results show that the proposed approach offers average retrieval precision as high as 88.59% after three iterations. Comprehensive comparisons with peer systems reveal that our system yields the highest retrieval accuracy after two iterations.